Unless otherwise indicated herein, the approaches described in this section are not prior art to the claims in this application and are not admitted to be prior art by inclusion in this section.
Consolidating the various data systems in a business enterprise (or any other organization) into a centralized data system is increasingly common. For example, the SAP HANA® database product provides advanced database technology such as an in-memory database engine that can allow the enterprise to store its most relevant data in main memory which enables analytics to be performed directly in the database.
However, an enterprise may maintain separate duplicate data systems for some of their operations. For example, a data system for facilities (e.g., manufacturing, sales, etc.) in the U.S. may be maintained separately from corresponding data system for facilities in Europe. Providing a set of data for each of the two data systems in a centralized data system may be implemented by creating multiple instances of a database schema for the separate data systems. Data modeling, however, then becomes a challenge because a data model is typically specific to a database schema. Managing multiple separate copies of a data model for each database schema can be time consuming from a development point of view and can be error prone when new versions of the data model become available and new copies need to be redeveloped.